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            <div class="highlight"><pre><span class="lineno">1</span><span></span><span class="kn">import</span> <span class="nn">math</span>
<span class="lineno">2</span>
<span class="lineno">3</span><span class="kn">import</span> <span class="nn">torch</span>
<span class="lineno">4</span><span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">nn</span>
<span class="lineno">5</span>
<span class="lineno">6</span><span class="kn">from</span> <span class="nn">labml_helpers.module</span> <span class="kn">import</span> <span class="n">Module</span>
<span class="lineno">7</span><span class="kn">from</span> <span class="nn">labml_nn.transformers</span> <span class="kn">import</span> <span class="n">MultiHeadAttention</span></pre></div>
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            <h2>අවකාශීයගැඹුර නැණවත් සම්මුතිය</h2>
<p>මෙයඇත්ත වශයෙන්ම මන්දගාමී ය</p>

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            <div class="highlight"><pre><span class="lineno">10</span><span class="k">class</span> <span class="nc">SpatialDepthWiseConvolution</span><span class="p">(</span><span class="n">Module</span><span class="p">):</span></pre></div>
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            <ul><li><code  class="highlight"><span></span><span class="n">d_k</span></code>
 එක් එක් හිසෙහි නාලිකා ගණන වේ</li></ul>

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            <div class="highlight"><pre><span class="lineno">17</span>    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">d_k</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">3</span><span class="p">):</span></pre></div>
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        <div class='code'>
            <div class="highlight"><pre><span class="lineno">21</span>        <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
<span class="lineno">22</span>        <span class="bp">self</span><span class="o">.</span><span class="n">kernel_size</span> <span class="o">=</span> <span class="n">kernel_size</span></pre></div>
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            <p>අපිපයිටෝර්ච් <code  class="highlight"><span></span><span class="n">Conv1d</span></code>
 මොඩියුලය භාවිතා කරමු. එක් එක් නාලිකාව සඳහා වෙනම සංවහනයක් (විවිධ කර්නල් සමඟ) සිදු වන පරිදි නාලිකා ගණනට සමාන වන පරිදි කණ්ඩායම් ගණන අපි සකස් කරමු. අපි දෙපැත්තටම පුරවන එකතු කර පසුව නිවැරදි වඩාත්ම <code  class="highlight"><span></span><span class="n">kernel_size</span> <span class="o">-</span> <span class="mi">1</span></code>
 ප්රති </p>. ල ලබා ගනිමු

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">27</span>        <span class="n">rng</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">math</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">kernel_size</span><span class="p">)</span>
<span class="lineno">28</span>        <span class="bp">self</span><span class="o">.</span><span class="n">kernels</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Parameter</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">kernel_size</span><span class="p">,</span> <span class="n">d_k</span><span class="p">))</span><span class="o">.</span><span class="n">uniform_</span><span class="p">(</span><span class="o">-</span><span class="n">rng</span><span class="p">,</span> <span class="n">rng</span><span class="p">))</span></pre></div>
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            <p> <code  class="highlight"><span></span><span class="n">x</span></code>
 හැඩය ඇත <code  class="highlight"><span></span><span class="p">[</span><span class="n">seq_len</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">heads</span><span class="p">,</span> <span class="n">d_k</span><span class="p">]</span></code>
</p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">30</span>    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">):</span></pre></div>
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    <div class='section' id='section-6'>
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                <a href='#section-6'>#</a>
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        <div class='code'>
            <div class="highlight"><pre><span class="lineno">35</span>        <span class="n">res</span> <span class="o">=</span> <span class="n">x</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">kernels</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">)</span>
<span class="lineno">36</span>
<span class="lineno">37</span>        <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">kernels</span><span class="p">)):</span>
<span class="lineno">38</span>            <span class="n">res</span><span class="p">[</span><span class="n">i</span><span class="p">:]</span> <span class="o">+=</span> <span class="n">x</span><span class="p">[:</span><span class="o">-</span><span class="n">i</span><span class="p">]</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">kernels</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">)</span>
<span class="lineno">39</span>
<span class="lineno">40</span>        <span class="k">return</span> <span class="n">res</span></pre></div>
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    <div class='section' id='section-7'>
        <div class='docs doc-strings'>
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                <a href='#section-7'>#</a>
            </div>
            <h2>බහු-Dconv-හිසඅවධානය (MDHA)</h2>
<p>අපි <a href="../mha.html#MHA">බහු-ප්රධාන අවධානය</a> අපගේ මුල් ක්රියාත්මක කිරීම දීර් and කරන අතර විමසුම, යතුර සහ වටිනාකම් ප්රක්ෂේපණ සඳහා අවකාශීය ගැඹුර-නැණවත් සම්මුතිය එක් කරමු. </p>

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        <div class='code'>
            <div class="highlight"><pre><span class="lineno">43</span><span class="k">class</span> <span class="nc">MultiDConvHeadAttention</span><span class="p">(</span><span class="n">MultiHeadAttention</span><span class="p">):</span></pre></div>
        </div>
    </div>
    <div class='section' id='section-8'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-8'>#</a>
            </div>
            
        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">51</span>    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">heads</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">d_model</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">dropout_prob</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.1</span><span class="p">):</span>
<span class="lineno">52</span>        <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">heads</span><span class="p">,</span> <span class="n">d_model</span><span class="p">,</span> <span class="n">dropout_prob</span><span class="p">)</span></pre></div>
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    <div class='section' id='section-9'>
        <div class='docs'>
            <div class='section-link'>
                <a href='#section-9'>#</a>
            </div>
            <p><a href="../mha.html#MHA">බහු-ප්රධාන අවධානය</a> විමසුම නිර්මාණය කරනු ඇත, ප්රධාන සහ අගය ප්රක්ෂේපනය මොඩියුල <code  class="highlight"><span></span><span class="bp">self</span><span class="o">.</span><span class="n">query</span></code>
<code  class="highlight"><span></span><span class="bp">self</span><span class="o">.</span><span class="n">key</span></code>
, සහ <code  class="highlight"><span></span><span class="bp">self</span><span class="o">.</span><span class="n">value</span></code>
. </p>
<p>අපිඔවුන් එක් එක් කිරීමට අවකාශීය ගැඹුර-නැණවත් convolution ස්ථරය ඒකාබද්ධ හා වෙනුවට <code  class="highlight"><span></span><span class="bp">self</span><span class="o">.</span><span class="n">query</span></code>
<code  class="highlight"><span></span><span class="bp">self</span><span class="o">.</span><span class="n">key</span></code>
, සහ <code  class="highlight"><span></span><span class="bp">self</span><span class="o">.</span><span class="n">value</span></code>
. </p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">59</span>        <span class="bp">self</span><span class="o">.</span><span class="n">query</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">query</span><span class="p">,</span> <span class="n">SpatialDepthWiseConvolution</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">d_k</span><span class="p">))</span>
<span class="lineno">60</span>        <span class="bp">self</span><span class="o">.</span><span class="n">key</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">key</span><span class="p">,</span> <span class="n">SpatialDepthWiseConvolution</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">d_k</span><span class="p">))</span>
<span class="lineno">61</span>        <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">SpatialDepthWiseConvolution</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">d_k</span><span class="p">))</span></pre></div>
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